Communicating via text message services such as short message service (SMS), e-mail, instant messaging, etc., is very popular and plays an increasingly important role in our life.
One popular way of communicating these text messages is by using some kind of handheld communication device such as a mobile phone, a PDA, a palmtop computer, etc. However, entering text messages into these handheld communication devices is often a cumbersome work. While some computing and communication devices, such as personal computers, palmtop computers, and some mobile phones have been equipped with a full QWERTY keyboard for alphanumeric text entry, many other computing and communication apparatuses, such as mobile phones, PDAs, and PDTs, are equipped with a limited or no keyboard. Entering text into computing and communication apparatuses with a limited or no keyboard can be done in several ways. If the apparatus have no keyboard or keys the text can be entered by either writing the text on a special surface, e.g. the screen of the apparatus, with a stylus, or by tapping on a virtual keyboard displayed on the apparatuses screen. Text entering using a keyboard with a limited number of keys is often done by pressing a key a varying number of times, generally within a limited period of time, to input a specific letter. This technique is known as multi-tap. However, entering text with multi-tap or with a stylus is quite cumbersome for the user, especially if large quantities of text are going to be entered. Therefore, a number of text entering systems have been developed to facilitate and to speed-up the text entering. These systems, often referred to as single-tap system with predictive text technologies, uses predictive letter patterns to allow the user to enter text by press the keys as few times as possible.
The predictive text system uses a predictive text dictionary to “intelligently guess” which character(s) or word(s) the user is about to enter. The predictive text dictionary essentially contains a list of character strings, words, acronyms, abbreviations, etc. that is used to predict which word that is being entered by the user. When entering text using multi-tap or single-tap there may be several words that match a given keystroke (character) sequence. The predictive text system may then select the best match(es), i.e. making a priority list of matching words, based on information about word frequency in the used language or word frequency in the users idiolect.
However, there is still a need for improved features related to text input.